Stepped frequency waveform for parameter definition for radar

Abstract

This document describes techniques, apparatus, and systems for parameter-defined stepped frequency waveforms for radar systems. A radar system transmits a radar transmit signal comprising a parameter-defined stepped frequency waveform having a specified frequency change between chirps. The specified frequency change can increase the signal-to-noise ratio of radar receive signals reflected by objects in a field of view. The radar receive signals can then be transformed into the frequency domain to determine ranges and range rates of objects in the field of view. The determined ranges and range rates from the representation of the radar receive signals in the frequency domain can be output to a radar tracker to enable tracking of objects in the field of view. In doing so, accurate radar tracking of objects in the field of view of the radar system can be generated that tracks robustly.

Description

Background Technology

[0001] Radar systems are commonly used as part of the perception system of autonomous vehicles to operate the vehicle or at least assist driving. Typically, a radar system receives signals reflected from objects in its field of view and processes them into useful information relating to relative position and velocity, enabling tracking of the object even when the vehicle-based radar and / or the object is moving. When the distance from the vehicle to the object changes frequently and / or by large amounts, noise in the reflected signals can introduce errors into the object measurements (e.g., position, orientation, and / or speed) output in object tracking. Inaccurate radar tracking, especially in dynamic everyday driving conditions, can lead to unsafe and / or uncomfortable driving behavior. Summary of the Invention

[0002] This document describes the techniques, apparatus, and systems for parameter-defined stepped frequency waveforms used in radar. A radar system transmits a radar signal comprising a parameter-defined stepped frequency waveform. The parameters of the radar system specify the frequency variations between each chirp. These specified frequency variations increase the signal-to-noise ratio of the radar received signal reflected by an object in the field of view. The received radar signal can be transformed into the frequency domain to determine the range and range rate of an object in the field of view. Determining the range and range rate of change based on the frequency domain is more accurate than deriving them in other ways, such as using other stepped waveforms. The range and range rate of change determined in the frequency domain can be output to a radar tracker to achieve high-accuracy tracking of objects in the field of view. In doing so, accurate radar tracking can be generated even with frequent or significant changes in the relative position of another object, for use in safe vehicle operation.

[0003] Among various aspects, a method is disclosed that includes transmitting a radar transmitted signal representing a parameter-defined step-frequency waveform comprising one frame of chirp. The pulse variation between the initial chirp and the current chirp can be defined based on the initial chirp's start frequency, the initial chirp's slope, the current chirp's index, and the pulse repetition period of the initial chirp. The method may further include receiving a radar signal representing a parameter-defined step-frequency waveform reflected by an object in the radar system's field of view, and the method further includes performing a transformation on the received radar signal to determine its representation in the frequency domain. Subsequently, the range and range change rate associated with the object in the field of view can be determined based on the frequency domain representation of the received radar signal, and the range and range change rate can be output to a radar tracker to achieve radar tracking of the object in the field of view.

[0004] In some implementations, performing a transformation of the radar received signal to determine its representation in the frequency domain includes performing a two-dimensional Fourier transform of the radar received signal to generate a two-dimensional representation of the radar received signal in the frequency domain. In various aspects, the two-dimensional representation includes a fast time dimension and a slow time dimension. In some implementations, determining the range and range change rate associated with an object in the field of view based on the frequency domain representation of the radar received signal includes determining the peak value of the two-dimensional representation of the radar received signal, and determining the range and range change rate corresponding to the peak value of the two-dimensional representation of the radar received signal. In various aspects, determining the range and range change rate corresponding to the peak value of the two-dimensional representation of the radar received signal includes determining the fast time frequency and slow time frequency associated with the peak value of the two-dimensional representation of the radar received signal, and determining the range and range change rate associated with the peak values ​​of the fast time frequency and the slow time frequency.

[0005] In some implementations, performing a transformation of the radar received signal to determine its representation in the frequency domain further includes compensating for the phase contribution of the radar received signal in the slow time dimension based on the range value of the two-dimensional representation of the radar received signal. In various aspects, determining the range and rate of change of range associated with an object in the field of view based on the frequency domain representation of the radar received signal includes ignoring second-order terms.

[0006] In some implementations, the method is executed by a system comprising a radar system, at least one processor, and at least one computer-readable storage medium. In various aspects, the computer-readable storage medium includes machine-readable instructions that, when executed by the at least one processor, cause the at least one processor to perform the disclosed method. In some implementations, the system includes a radar system for a vehicle. In various aspects, the system outputs distance and rate of change of distance to a radar tracker that performs radar tracking to assist in the execution of vehicle functions. In some implementations, the described operations are executed on multiple processors. For example, portions of the described techniques may be executed on a single processor, while others may be executed on separate processors. Additionally, the processors, computer-readable storage medium, vehicle subsystems, radar system components, etc., may communicate via a data bus. In some implementations, portions of a step-frequency waveform defined by the parameters of the radar system are executed by a waveform generator or radar processing component. The waveform generator or radar processing component may include hardware, software, or firmware configured to perform the techniques described above.

[0007] This invention provides a simplified concept related to two-dimensional signal processing for motion compensation in radar systems, which is further described in the detailed embodiments and accompanying drawings. This invention is not intended to identify essential features of the claimed subject matter, nor is it intended to define the scope of the claimed subject matter. Attached Figure Description

[0008] This document describes in detail one or more aspects of the stepped frequency waveform used for parameter definition of a radar system, with reference to the following figures. Throughout the figures, the same numbers are generally used to refer to similar features and components: Figure 1 An example environment for step frequency waveforms for parameter definition used in a radar system is shown; Figure 2 An example vehicle is shown, comprising a system configured to utilize a stepped frequency waveform defined for parameters of a radar system; Figure 3 An example radar system is shown, comprising a system configured to utilize a stepped frequency waveform defined for parameters of the radar system. Figure 4 An example of a stepped frequency waveform for parameter definition in a radar system is shown; Figure 5 An example method for defining step frequency waveforms for parameters used in radar systems is shown. Figure 6 Example results of a general-purpose stepped-frequency waveform for radar systems are shown; and Figure 7 Example results of stepped frequency waveforms for parameter definition of a radar system are shown. Detailed Implementation introduction

[0009] A perception system can rely on a radar tracker to provide situational awareness and detect objects of interest in the environment of a vehicle. The radar system includes a transmit-receive antenna array, such as a multiple-input multiple-output (MIMO) antenna array and a MIMO integrated circuit (MMIC), which acquires multiple chimes of radar echoes reflected from objects over multiple (time) frames. Based on the radar data output by the MMIC, a radar processor can transform the radar data to the frequency domain using a two-dimensional Fourier transform (e.g., a discrete Fourier transform (DFT) or a fast Fourier transform (FFT)). In the frequency domain, the radar signal can be represented in both a fast time dimension (e.g., samples collected within a single chime) and a slow time dimension (e.g., samples collected across multiple chimes). When the received signal is transformed to the frequency domain, the received energy from the radar signal reflection can be better grouped to identify energy peaks within the two-dimensional FFT. Detection can be determined based on the energy peaks of the radar signal reflected by objects in the radar system's field of view. Detection can include data such as range and rate of change of range, determined by a system of linear equations and associated with the radar reflection portion of an object over a specific time period. However, certain terms in the phase response of the radar received signal can increase noise in the frequency domain and contribute to errors in the calculation of range and rate of change of range, or result in incomplete detection of objects in the field of view. Therefore, radar tracking generated from a noisy phase response may be inaccurate, leading to inaccurate or incomplete driving tracking.

[0010] Radar trackers can infer object measurements (object position, size, orientation, velocity, and acceleration) based on a small subset of detections of each object in a scene. Some detections can be discarded (e.g., considered noise) to reduce the amount of radar data ultimately processed. Detections can be discarded by applying thresholding and / or by applying non-maximum suppression of the energy attributed to the detection (e.g., by searching for peaks in the frequency domain). Thus, a radar tracker can produce a track that includes measurements associated with objects in the field of view that receive signals from reflected radar. However, if the data associated with the detections (e.g., distance and rate of change of distance) is inaccurate or completely missing, the radar tracker may produce inaccurate radar tracking, which could lead to unsafe, uncomfortable, or unstable driving behavior when relying on such inaccurate radar tracking to perform vehicle functions. Overview

[0011] This document describes techniques, apparatus, and systems for using parameter-defined stepped-frequency waveforms for radar. An example radar system generates and transmits a radar transmit signal, the radar reflective signal of which includes a predetermined stepped-frequency waveform. The radar transmit signal is transmitted within the radar system's field of view, and the radar receive signal is received by the radar system's receiver. The radar receive signal can be used to generate a two-dimensional representation of the received radar signal in the frequency domain (e.g., a fast time dimension and a slow time dimension). In some examples, the use of parameter-defined stepped-frequency waveforms creates a range value based on the two-dimensional representation to compensate for the slow time dimension. Once created, the two-dimensional representation of the received radar signal can be searched to obtain energy peaks (e.g., points on the two-dimensional representation that meet certain criteria). Due to the use of parameter-defined stepped-frequency waveforms, the energy peaks can have a greater signal-to-noise ratio because terms in the phase response of the radar receive signal are eliminated.

[0012] Once the energy peak is determined in a two-dimensional representation, data associated with the energy peak can be derived. For example, distance and the rate of change of distance can be determined using a system of linear equations that correlate frequencies in the fast time dimension with frequencies in the slow time dimension. The use of parameter-defined step-frequency waveforms allows for more accurate determination of distance and the rate of change of distance based on the detection of objects in the field of view. Therefore, more accurate radar tracking can be determined by utilizing more accurate object position, object orientation, and / or object velocity by a radar tracker. In some implementations, distance and the rate of change of distance can be output to a vehicle subsystem to perform vehicle functions. In some implementations, distance and the rate of change of distance are used to generate tracking, which is used by an advanced driver assistance system to detect and avoid objects. In this way, the techniques, apparatus, and systems described herein can provide safe, comfortable, and convenient autonomous vehicle operation. Example Environment

[0013] Figure 1 An example environment 100 for a stepped frequency waveform used in a radar system is shown. In the depicted environment 100, a vehicle 102 is traveling on a road. Although shown as a passenger car, vehicle 102 could represent other types of motorized vehicles (e.g., cars, motorcycles, buses, tractors, semi-trailers), non-motorized vehicles (e.g., bicycles), rail vehicles (e.g., trains), water vehicles (e.g., boats), aircraft (e.g., airplanes), or spacecraft (e.g., satellites), etc. Vehicle 102 relies on a sensing system including radar system 104 to avoid other objects that may be present in environment 100 while driving.

[0014] Radar system 104 outputs radar data, which includes indications of objects detected in field of view 106. For example, the radar data can warn advanced safety or autonomous driving systems of vehicle 102 about objects (e.g., object 108) appearing near vehicle 102. Radar system 104 can be mounted on, installed in, or integrated with any part of vehicle 102, such as the front, rear, top, bottom, or sides of vehicle 102, bumpers, side mirrors, headlights and / or taillights, or at any other internal or external location of vehicle 102 where radar is intended for object detection. Radar system 104 may include multiple radar devices or multiple radar systems that coordinate with each other to provide field of view 106.

[0015] Radar system 104 may include a combination of hardware components and software components executing thereon. For example, a computer-readable storage medium (CRM) of radar system 104 may store machine-executable instructions that, when executed by a processor, cause radar system 104 to output information about objects detected in field of view 106. An example combination of hardware and software components of radar system 104 includes an MMIC 112, at least one processor 114, a waveform generator 116, a radar processing component 118, and a radar tracker 120.

[0016] With the inclusion of MMIC 112, radar system 104 is shown as a MIMO radar system; however, the radar tracking techniques described herein are not limited to MIMO radar systems but can be applied to radar tracking in radar systems of other radar types. For simplicity of the figures, the antenna is not shown; however, MMIC 112 includes an interface to a suitable antenna, such as a MIMO antenna array. During each time frame, MMIC 112 transmits radar signal 110-1 via the antenna to radiate objects in the field of view 106. MMIC 112 receives radar echo 110-2 as a reflected version of the radar signal 110-1 transmitted for that frame via the antenna. MMIC 112 converts radar echo 110-2 into a digital format so that radar system 104 can quickly establish tracking of objects in the field of view 106.

[0017] Processor 114 and waveform generator 116 are configured to generate a waveform for transmitting radar signal 110-1. In various respects, waveform generator 116 generates a stepped-frequency waveform based on a predetermined set of parameters. In doing so, the signal-to-noise ratio of the received radar echo 110-2 in the spectrum can allow for more accurate radar detection. Waveform generator 116 may contain computer-readable instructions that, when executed by processor 114, cause processor 114 to operate communicatively with MMIC 112. For example, processor 114 may execute waveform generator 116 to determine an ideal waveform based on defined parameters and provide that ideal waveform to MMIC 112. MMIC 112 may perform modulation, multiplexing, or any other signal manipulation. Although the above process is described as being executed on processor 114 by executing waveform generator 116, it should be understood that waveform generator 116 can be implemented by any combination of hardware, software, or firmware.

[0018] Processor 114, radar processing component 118, and radar tracker 120 are configured to process radar echoes 110-2 digitized by MMIC 112 into various forms of other radar data. Some of these other forms of radar data are maintained for internal use within radar system 104, such as a set of detections 122. Other forms of radar data are generated for use by other systems of vehicle 102 (outside radar system 104), such as a set of tracks 124 corresponding to objects tracked from radar echoes 110-2 against field of view 106.

[0019] Processor 114 generates a two-dimensional representation of the received radar signal, which indicates a set of measurements associated with the digitized radar echo 110-2 obtained from MMIC 112 during one or more frames. In some implementations, the two-dimensional representation may be adjusted for phase contributions due to range in the slow time dimension. Based on the two-dimensional representation of the digitized radar echo 110-2 obtained from MMIC 112, processor 114 may perform peak finding. Radar processing component 118 may utilize the found peaks to generate detections 122. A single detection or a set of detections 122 may indicate the range and radial range change rate relative to the effective radar echo 110-2 (scattered) on object 108 in environment 100. Detections 122 may have errors in location (e.g., azimuth); however, numerous detections of accurate and high-quality range and range change rate among the detections 122 can be used to support enhancements to tracking 124. Thus, detections 122 containing more accurate data (e.g., range and range change rate) can facilitate more accurate tracking 124.

[0020] Radar processing component 118 can analyze and determine the data associated with detection. For example, a peak can be found within a two-dimensional representation of the digitized radar echo 110-2. In the frequency domain, the peak can be identified based on its location in both the fast time dimension (e.g., samples collected within a single chirp) and the slow time dimension (e.g., samples collected within multiple chirs). Based on the frequencies identified in each of the corresponding domains, a system of two-dimensional equations concerning range and range change rate can be created. This system of equations can be solved by radar processing component 118, thus determining the range and range change rate data associated with the found peak. Due to the parameter-defined step-frequency waveform, the two-dimensional representation can maintain a high signal-to-noise ratio even at high relative velocities between radar system 104 and object 108. As a result, detection 122 can be determined more accurately from the two-dimensional representation, and the range and range change rate associated with the peak in the two-dimensional representation can be determined more precisely.

[0021] An object can be detected from the analysis of detection 122. Detection 122 can be resolved into object data based on the detection when radar tracker 120 is executed. This object data can be maintained internally within radar system 104 to enable the subsequent generation of tracking 124. Object data differs from tracking 124, which is a high-accuracy representation of an object enhanced by radar detection. Instead, object data refers to the internal representation of an object (or a portion of an object) and its corresponding measurements, which are maintained until they can be used to establish or enhance tracking 124.

[0022] Radar tracker 120 can generate object data derived from detections 122, for example, by grouping and analyzing the detections 122 using detection-based object recognition techniques. Some of the detections 122 (e.g., false detections, noise) can be filtered to reduce the complexity / number of detections 122 ultimately processed. For example, detections 122 can be discarded by thresholding and / or by applying non-maximum suppression of the energy attributed to the detection (e.g., by searching for peaks in the range-Doppler plane). Throttling can filter out false detections more accurately while filtering out detections 122 by utilizing a parameter-defined step-frequency waveform. Example vehicle configuration

[0023] Figure 2An example vehicle 102-1 is shown, comprising a system configured to utilize a stepped frequency waveform for a radar system. Vehicle 102-1 is an example of vehicle 102. Included in vehicle 102-1 is radar system 104-1, which is an example of radar system 104 shown in more detail. Vehicle 102-1 includes a vehicle-based system 200, which is operatively and / or communicatively coupled to radar system 104-1 via link 202. Link 202 may be one or more wired and / or wireless links, including vehicle-based network communication for interconnecting components of vehicle 102-1. In some examples, link 202 is a vehicle communication bus.

[0024] Vehicle-based system 200 uses radar data provided by radar system 104-1 on link 202 to perform specific functions. For example, a set of tracks 124 may include information about the movement of objects in the field of view, such as the speed and positional changes of object 108, to enable vehicle-based system 200 to control vehicle 102-1 to perform emergency braking, lane changes, or adjust the direction and / or speed of the vehicle. In another example, detection 122 may be provided separately to vehicle-based system 200 to perform object detection. In example use, object detection may be used as part of blind spot monitoring in vehicle safety. Examples of vehicle-based system 200 include systems for autonomous control 206-1, safety 206-2, positioning 206-3, vehicle-to-vehicle communication 206-4, occupant interface 206-5, and multi-sensor trackers 206-6. Other examples of vehicle-based system 200 may be envisioned as including its vehicle subsystems (e.g., components, circuitry). The radar data output to the vehicle-based system 200 on link 202 includes tracking 124 generated by radar tracker 120-1 of radar system 104-1 (e.g., an example of radar tracker 120). Tracking 124 includes object-level information corresponding to an object detected in field of view 106, which, upon being received by the vehicle-based system 200, enables vehicle 102-1 to drive safely by avoiding object 108.

[0025] As an example, the autonomous control 206-1 provided by the vehicle-based system 200 can autonomously or semi-autonomously control the vehicle 102-1 and drive safely on the road using a set of tracks 124 received via link 202. The vehicle-based system 200 can perform other functions in response to the set of tracks 124, which are not necessarily for vehicle control. For example, the set of tracks 124 can be output to the occupant interface 206-5 to allow the operator or controller to take action and avoid objects. The set of tracks 124 can be provided to other vehicles using vehicle-to-vehicle communication 206-4 to allow the operator or controller of the other vehicle to also avoid the tracked object, or to ensure that vehicle 102-1 is aware of the presence of other vehicles. By improving situational awareness, vehicle 102-1 can drive more safely, avoiding object 108 and other objects in the environment 100.

[0026] Radar system 104-1 includes MMIC 112-1 (as an example of MMIC 112). MMIC 112-1 includes transmitter / receiver element 210, timing / control element 212, and analog-to-digital converter 214. For simplicity of the figures, from... Figure 2 The MIMO antenna array, which is also part of the radar system 104-1, is omitted here and is operatively coupled to the transmitter / receiver element 210.

[0027] Transmitter / receiver element 210 is configured to transmit an electromagnetic (EM) signal as a radar signal (e.g., radar signal 110-1) and receive a reflected version of the EM signal (e.g., radar echo 110-2). In MIMO examples like this, transmitter / receiver element 210 is capable of receiving radar echoes at a higher resolution than, for example, multi-state radar. Transmitter / receiver element 210 includes one or more components for transmitting the EM signal and one or more components for detecting the EM signal. Transmitter / receiver element 210 enables the transmission of a radar signal radiating a field of view, as well as the management of the reception of radar echoes, many of which correspond to object reflections of the transmitted radar signal. Transmitter / receiver element 210 can be configured as a transceiver implemented as a single component (e.g., a chip) to perform both transmission and reception. Alternatively, transmitter / receiver element 210 can be implemented as a separate transmitter and a separate receiver.

[0028] The timing / control element 212 performs operations to effectively track radar signals, such as adjusting the characteristics (e.g., frequency, gain, phase, period) of the transmitted radar signal or capturing the reflected radar echo. For example, according to existing MIMO technology, the timing / control element 212 causes the transmitter / receiver element 210 to adjust the size, shape, antenna pattern, or other characteristics of the radar system 104-1 to transmit radar signal 110-1, thereby enabling the radar echo 110-2 to capture high-resolution information about the environment 100.

[0029] Analog-to-digital converter 214 converts the radar echo received from transmitter / receiver element 210 into a digital form that can be used to generate data cube 216, detection 122, and other radar processing. MMIC 112-1 samples the signal at an appropriate sampling rate (e.g., at least a Nyquist frequency). MMIC 112-1 outputs the digitized radar echo via link 208, which represents an internal communication link between the components of radar system 104-1. Link 208 can be wired or wireless and allows the internal representation of radar data to be exchanged within radar system 104-1 before being presented as tracking 124 output on link 202.

[0030] Radar system 104-1 is operatively coupled to MMIC 112-1 and link 208. Radar system 104-1 also includes at least one processor 114-1, which is an example of processor 114. Some examples of processor 114-1 include controllers, control circuitry, microprocessors, chips, systems, system-on-a-chip (SoC), devices, processing units, digital signal processing units, graphics processing units, and central processing units. Processor 114-1 can be any component configured to process digitized radar echo frames obtained from MMIC 112-1 to communicate objects in the field of view based on information appearing in track 124. Processor 114-1 may include multiple processors, one or more chips, embedded memory or firmware storing software, caches, or any other computer element that enables processor 114-1 to execute machine-readable instructions for generating track 124.

[0031] Machine-readable instructions executed by processor 114-1 may be stored in a computer-readable medium (CRM 204) of radar system 104-1. CRM 204 may also be used to store data managed by processor 114-1 during instruction execution. In some examples, CRM 204 and processor 114-1 are a single component, such as a SoC including CRM 204 with dedicated memory configured for processor 114-1. In some examples, access to CRM 204 is shared by other components of radar system 104-1 connected to CRM 204, for example via link 208 (e.g., MMIC 112-1). Processor 114-1 obtains instructions from CRM 204, and execution of these instructions configures processor 114-1 to perform radar operations. Example radar operations include signal processing and radar tracking, which result in tracking 124 being transmitted via link 202 to vehicle-based system 200 and other components of vehicle 102-1. In this example, CRM 204 may include instructions for configuring processor 114-1 to generate data cube 216, generate detection 122, and resolve data cube 216 and detection 122 into track 124. For example, CRM 204 includes instructions for executing radar processing component 118-1, which is an example of radar processing component 118. CRM 204 also includes an instruction set that, when executed by processor 114-1, implements waveform generator 116-1, radar processing component 118-1, and radar tracker 120-1, which are examples of waveform generator 116, radar processing component 118, and radar tracker 120, respectively.

[0032] When executed by processor 114-1, waveform generator 116-1 generates a stepped-frequency waveform based on defined parameters, or commands MMIC 112-1 to generate a stepped-frequency waveform based on defined parameters. In various aspects, waveform generator 116-1 can provide instructions for causing the waveform to be generated from MMIC 112-1, where the waveform can undergo any number of signal operations, such as modulation, multiplexing, filtering, etc. MMIC 112-1 can then output the waveform to a transmitting antenna array that transmits radar signals within the target's field of view.

[0033] The transmitted radar signal may include a waveform generated using waveform generator 116-1, and as a result, radar echoes reflected by objects in the field of view can be processed with a higher signal-to-noise ratio. It should be understood that although processor 114-1 is shown as executing waveform generator 116-1, waveform generator 116-1 and processor 114-1 can be implemented together, for example, as a SoC. Furthermore, waveform generator 116-1 may include any other combination of fixed logic circuitry systems and is implemented wholly or partially in hardware, software, or firmware.

[0034] When executed by processor 114-1, radar processing component 118-1 determines a two-dimensional representation of the digitized radar echo output by MMIC 112-1 in the frequency domain. For example, radar processing component 118-1 can use a Fourier transform to convert the digitized radar echo in the time domain output by MMIC 112-1 into a two-dimensional representation of the radar echo in the frequency domain. The two-dimensional representation may include a fast time dimension corresponding to samples collected within a single chirp and a slow time dimension corresponding to samples collected within multiple chirs. Radar processing component 118-1 can compensate for the two-dimensional representation in the slow time dimension based on the phase contribution of the range values ​​in the two-dimensional representation. In some cases, phase compensation due to range is required due to the use of parameterized step-frequency waveforms. In some implementations, the radar processing component can determine all range values ​​smaller than the two-dimensional representation in the range values ​​to perform compensation. This portion of the range values ​​may correspond to significant ranges in a particular radar frame. In various aspects, reducing phase compensation to a portion of the range values ​​reduces computation time and processing complexity.

[0035] Once the two-dimensional representation of the radar echo in the frequency domain is determined, radar processing component 118-1 can operate on the peaks of the two-dimensional representation (e.g., peaks found through peak search). In doing so, radar processing component 118-1 can use the frequencies of the peaks found in the fast time dimension and the frequencies of the peaks found in the slow time dimension to solve a system of two-dimensional equations concerning the range and range change rate associated with the found peaks. In all respects, the radar processing component 118-1 determines the peaks more accurately due to the increased signal-to-noise ratio caused by the step-frequency waveform determined by the transmission parameters. Therefore, object detection or range and range change rate calculations for objects in the field of view can be more accurate. Radar processing component 118-1 can output the detected object, range, or range change rate to radar tracker 120-1 in the form of detection 122 or according to data cube 216. Alternatively, or additionally, radar processing component 118-1 can output the object detection, range, or range change rate directly to vehicle-based system 200 to assist in the execution of the functions of vehicle 102-1.

[0036] Radar tracker 120-1 can output tracking 124. Radar tracker 120-1 can act on detection 122, data cube 216, or both. In a specific implementation, radar tracker 120-1 acts on detection 122 by grouping or clustering the detection 122 to detect objects. Object data may include informational data (e.g., distance, rate of change of distance, azimuth) that can be used to generate tracking 124. Tracking 124 can be generated based on any number of detections 122, including a single detection 122 or a group of detections 122. Each of tracking 124 may include object measurements indicating information about the object (such as position, movement, or other attributes). By providing more accurate data from radar processing component 118-1, tracking 124 can have higher accuracy and reliability for performing actions of vehicle-based system 200. Tracking 124 can be updated as radar system 104 captures additional radar echoes over multiple frames. Generally, each of tracking 124 includes object-level information corresponding to an object reflected by radar across the entire field of view. Each of the tracks 124 can have a structure that includes a number of fields containing various attributes estimated for a particular object. The tracks 124 can be provided to any component of the vehicle 102-1 or radar system 104-1, including any system in the vehicle-based system 200. Example radar system

[0037] Figure 3 An example radar system 104-2 is shown, comprising a system configured to utilize a stepped-frequency waveform defined for parameters of a radar system. Radar system 104-2 is an example of radar system 104. Radar system 104-2 is shown as including MMIC 112-2 (an example of MMIC 112). MMIC 112-2 is connected to receiving antenna 300. Examples of receiving antennas may include MIMO antenna arrays, but the stepped-frequency waveform defined for the parameters of the radar system can be applied to any radar system. Therefore, it should be understood that receiving antenna 300 can be any number of radar receiving antennas.

[0038] Radar antenna 300 transmits a radar signal (e.g., radar signal 110-1) within the field of view of radar system 104-2. The radar signal may include a stepped-frequency waveform 302 defined using parameters determined by waveform generator 116-2. Waveform 302 may be controlled by a given equation, the parameters of which may be determined based on a specific waveform. For example, waveform 302 may include one or more frames (e.g., transmitted over time) of the radar signal. Each of the one or more frames may include a group with at least two chimes (e.g., a single pulse transmitted at a specific frequency), and the frequency variation between successive chimes (e.g., the current chime and the initial chime) may be specified by a predetermined equation. In various aspects, the frequency variation between successive chimes is based on the starting frequency of the initial chime in the chime group, the slope of the initial chime, the index of the current chime, and the pulse repetition period of the initial chime. By defining waveform 302 according to these parameters, coupling terms that contribute noise to the frequency domain representation of the radar echo can be eliminated. Therefore, waveform 302 can produce a higher signal-to-noise ratio in the frequency domain representation of the radar echo.

[0039] Waveform 302 can be provided to MMIC 112-2, where it can undergo any number of signal operations, such as modulation, multiplexing, filtering, etc. Waveform 302 can then be output by MMIC 112-2 to radar antenna 300, which transmits radar signals (e.g., radar signal 110-1) in the object's field of view. In this way, the transmitted radar signals can include waveform 302 generated using waveform generator 116-1, and as a result, radar echoes reflected by objects in the field of view can be processed with a higher signal-to-noise ratio. After radar antenna 300 transmits radar signals, they are reflected back to radar system 104-2 by objects in the field of view. Processor 114-2 (an example of processor 114) can execute transmit / receive (TX / RX) control 304, which controls the transmit and receive operations of MMIC 112-2. This can include any operation on waveform 302, such as digitization, modulation, multiplexing, or any other transceiver operation. In all aspects, the TX / RX control 304 allows the antenna 300 to operate as either a receiving antenna or a transmitting antenna.

[0040] Radar antenna 300 collects samples of received radar signals (e.g., radar echo 110-2). The radar transmitted signal may be reflected from an object, and the radar echo may include multiple chimes transmitted within one or more frames and received at radar antenna 300. As radar samples are collected over time, MMIC 112-2 can process the received radar echoes using an analog-to-digital converter to create a digitized received signal 306. The MMIC can output the digitized received signal 306 in the time domain, resulting in the energy associated with reflections from a single object (e.g., object 108) being represented at different time values.

[0041] Within radar system 104-2, radar processing component 118-2 can operate on processor 114-2. Processor 114-2 is an example of processor 114. Radar processing component 118-2 can take digitized received signal 306 as input and perform a Fourier transform (e.g., FFT or DFT) to convert digitized received signal 306 from the discrete time domain to the discrete frequency domain. In the frequency domain, the received radar signal reflected by a single object will return a signal with the same or similar frequency. Therefore, the energy received from multiple samples of multiple chimes transmitted within at least one frame can be collected and represented in terms of frequency relative to both the fast time dimension (e.g., samples collected within a single chime) and the slow time dimension (e.g., samples collected across multiple chimes). As described, the representation of the received radar signal is a two-dimensional representation relative to both the fast and slow time dimensions.

[0042] In various aspects, radar processing component 118-2 can compensate for the slow-time dimension of the two-dimensional representation of the radar received signal in the frequency domain for the phase contribution due to range. Specifically, the two-dimensional representation can be compensated for in the slow-time dimension based on the range value of the two-dimensional representation. In various aspects, phase compensation is based on the frequency change between the current chirp and the initial chirp, the range value of the two-dimensional representation, and the speed of light. In some implementations, radar system 104-2 can have a portion of interest in the range value. In this implementation, the slow-time dimension is compensated only for the range value within that portion of the range value. Therefore, compensation of the two-dimensional representation can require less processing power and less computation time. For example, radar system 104-2 can be used for blind spot detection, and thus primarily involves object detection within the blind spot range. In another example, radar system 104-2 can provide an estimate of the position of an object in the field of view and can determine the portion of the range value that contains that estimate. In either example, the slow-time dimension can be compensated only for the portion of interest in the range value. Alternatively, the slow time dimension can be compensated for for all distance values ​​within the instrumented range.

[0043] Radar processing component 118-2 can process the two-dimensional representation, for example, by performing peak estimation / search. Peak estimation searches the two-dimensional representation to obtain energy peaks, thereby distinguishing the radar reflection of objects in the field of view from system noise. Peak search can be performed using various interpretation methods. Radar processing component 118-2 can determine one or more energy peaks in the two-dimensional representation of the digitized received signal 306 for signal processing.

[0044] Radar processing component 118-2 is an example of radar processing component 118. Radar processing component 118-2 can find one or more energy peaks in a two-dimensional representation in the frequency domain and determine the data associated with one or more peaks. Because a parameter-defined step-frequency waveform is used, the two-dimensional representation in the frequency domain can have a higher signal-to-noise ratio after proper phase compensation, thus allowing for more accurate peak finding and filtering. The radar processing component 118-2 can determine frequencies in both the fast and slow time dimensions for the energy peaks, and these frequencies are used in a system of equations to determine the data associated with the energy peaks, including range and range change rate. For example, a system of equations can be used that includes two unknowns, range and range change rate. The two frequencies (e.g., in the fast and slow time dimensions) can be represented based on range and range change rate. Due to the high signal-to-noise ratio, the range and range change rate associated with the energy peaks and determined by the two-dimensional equations can be more accurate in terms of range and more precise in terms of range change rate.

[0045] Data associated with the energy peak (including range and rate of change of range) can be output to tracker 120-2. Radar tracker 120-2 is an example of radar tracker 120. As shown, the radar tracker operates on processor 114-3. It should be understood, however, that radar system 104-2 can operate on a single processor or multiple processors. Therefore, although shown as implemented on processor 114-3, radar tracker 120-2 can be implemented on the same processor (e.g., processor 114-2 or any other processor) as other components of radar system 104-2 (e.g., radar processing component 118-2, etc.).

[0046] In some implementations, the data associated with the energy peak is output in one of two ways: as a detection 122 or as a data cube 216 including the data. For example, detection 122 can be output as data including the distance and rate of change of distance associated with the energy peak. Thus, an object can be determined based on a single detection or multiple detections in detection 122. Detection 122 can be input to radar tracker 120-2, where the object's distance, rate of change of distance, and position enable radar tracker 118-2 to perform radar tracking. In one aspect, by providing a higher signal-to-noise ratio and more accurate distance and rate of change of distance determination through radar processing component 118-2, radar tracker 120-2 can perform more accurate radar tracking, even at high rates of change of distance. In another example, the data associated with the energy peak is included as part of data cube 216. Radar tracker 120-2 can input the data cube and perform object tracking based on the information available within data cube 216. In yet another example, both detector 122 and data cube 216 can be used to enable radar tracking via radar tracker 120-2. Alternatively, or additionally, detector 122 can be output directly along link 208 when radar tracking is not required. For example, in simple object detection.

[0047] Radar tracker 120-2 can perform radar tracking by generating internal radar tracking based on detection 122, data cube 216, or both. Radar tracking 124 can be output to any other element of radar system 104-2 or any system in a vehicle-based system (e.g., vehicle-based system 200). For example, radar tracker 120-2 can determine tracking 124 based on detection 122 or data cube 216 and output tracking 124 along link 202. Where the radar system is implemented on a vehicle (e.g., vehicle 102), link 202 can communicate with the vehicle subsystem to utilize tracking 124 to assist vehicle functionality.

[0048] As the radar signal acquires and processes additional radar echoes within multiple frames, the radar tracker 120-2 can update the track 124. The track 124 defines the location and other information about objects outside the radar system 104-2. In some instances, the radar tracker 120-2 may include a tracking filter function. When configured to perform the tracking filter function, the radar tracker 120-2 may include a measurement model, such as a nearly coordinated-turn constant-acceleration (CTCA) motion model, to model the dynamic behavior of the track 124. Any other suitable tracking filter motion model can be used by the radar tracker 120-2, such as Cartesian constant acceleration, or the coordinated-turn model can be paired with any suitable tracking filter method, such as an extended Kalman filter, an unscented Kalman filter, a probability hypothesis density (PHD) filter, a particle filter, etc.

[0049] Thus, the radar system 104-2 outputs a collection of highly accurate tracking 124 or highly accurate detection 122 of objects in the scene. The radar output may appear similar to that from other radar trackers; however, by using data (e.g., range and rate of change of range) associated with energy peaks determined according to a two-dimensional representation with a high signal-to-noise ratio, the tracking output from the radar system 104-2 can be more accurate than that from these other trackers. This technique does not require altering existing prediction models but rather leverages these and other radar software and hardware systems to provide plug-and-play enhancements. Some other radar systems can be replaced by the radar system 104-2 to more accurately convey tracking 124 or detection 122 using more accurate data from the radar processing component 118-2. Improving the accuracy and fidelity of the radar output in this way can improve the operation of perception systems that rely on radar output. In the case of autonomous driving functions or advanced safety features of vehicles (e.g., vehicle 102), the radar system 104-2 can be relied upon to safely maneuver vehicles on roads. Driving decisions supported by radar system 104-2 can lead to safe and comfortable vehicle behavior, which can improve driving safety for many categories of vehicles, such as low-cost, commercial, and luxury vehicles. Example waveform

[0050] Figure 4 An example of a stepped frequency waveform 302 for parameter definition in a radar system is shown. Specifically, Figure 4 Waveform 302 is shown relative to time and frequency. Frequency is displayed in gigahertz (GHz), while time is displayed in milliseconds (ms). Figure 4As shown, waveform 302 is a stepped-frequency waveform 302. Therefore, the frequency of the waveform varies with time. In various aspects, waveform 302 includes multiple chirps set within at least one frame. The frequency variation between consecutive chirps can be defined by parameters such that the resulting radar received signal has a high signal-to-noise ratio in the frequency domain.

[0051] Specifically, frequency variation can be defined as a coupling term that cancels out the phase representation of the radar echo, causing noise and spectrum broadening in the frequency domain. For example, the frequency variation between consecutive pulses can be defined by the following given equation: Where k is the chirp index, Δf(k) is the frequency change between the k-th chirp and the initial chirp, f0 is the frame start frequency or the frequency of the first chirp, S is the slope of the first chirp, and PRP is the pulse repetition period of the first chirp (e.g., the time between chirs). The pulse repetition period of each chirp can be changed when the chirp frequency is varied. For example, the pulse repetition period can decrease as the pulse index increases. In this example, the chirp is sent more frequently as the frame continues.

[0052] The delay time of a given pulse can be defined relative to the start of a frame. Specifically, the time delay of the k-th chirp can be defined by the following equation: Where T k Δf(k) is the delay time of the k-th chirp, k is the chirp index, Δf(k) is the frequency change between the k-th chirp and the initial chirp, f0 is the start frequency of the frame or the frequency of the first chirp, and PRP is the pulse repetition period of the first chirp (e.g., the time between chirs). Example Method

[0053] Figure 5 An example method 500 for defining a stepped frequency waveform for a radar system is shown. Operations (or steps) 502 to 510 are performed, but are not necessarily limited to the order or combination of operations shown herein. Furthermore, any one or more operations may be repeated, combined, or rearranged to provide other operations. For ease of description, refer to... Figure 1 The element describes method 500.

[0054] At point 502, radar system 104 transmits radar signal 110-1 representing a stepped frequency waveform. Radar signal 110-1 can be transmitted over multiple frames (e.g., over time), each frame comprising multiple chimes (e.g., pulses). The number of chimes per frame can be varied based on design requirements. For example, a higher number of chimes per frame can produce a higher signal-to-noise ratio and allow detection at greater distances. However, a higher number of chimes per frame may also increase the data complexity and computation time for radar processing. Radar signal 110-1 includes at least two chimes, defined with a frequency variation based on the starting frequency (f0), a slope (S) of the first chime, a chime index (k), and a pulse repetition period (PRP) of the first chime. Specifically, the phase response of radar echo 110-2 can be expressed as the following equation: in, In the above equation, Φ IF This represents the phase response of the radar echo, where m is the index of the sample within the chirp, fs is the sampling frequency, R is the target range, v is the rate of change of the target range, and T... k It is the delay time at the start of the k-th chirped frame. In all aspects, the target distance and the rate of change of target distance are unknowns, which can be solved to determine the distance and rate of change of distance of objects in the field of view. This equation can be extended in the following form:

[0055] According to this equation, these terms can be decomposed based on their contribution to the two-dimensional Fourier transform, which converts the radar echo back to frequency space. Therefore, the phase response can be decomposed into constant terms, terms contributing to the fast time dimension, terms contributing to the slow time dimension, and coupling terms. When the phase response is decomposed into contributing terms, coupling terms are shown to cause spectral spread, or a decrease in signal level in the two-dimensional Fourier transform of the radar echo. In some instances, spectral spread or increased noise is more pronounced at higher rates of range change.

[0056] To reduce spectral spread caused by coupling terms, coupling terms can be eliminated by defining the frequency variation between the current chirp and the initial chirp in a way that eliminates coupling terms. For example, the following relationship can be defined to eliminate coupling terms: By rearranging the above equations and solving for Δf(k), the waveform can be defined using the frequency change of the current chirp relative to the initial chirp, as shown below:

[0057] By defining the waveform in this way, the signal-to-noise ratio of the reflected radar echo 110-2 can be increased in the spectrum, even at high range change rates, and spectral broadening can be eliminated. In various aspects, the waveform is generated by the processor 114 through the execution of the waveform generator 116. The transmitted radar signal 110-1 can represent a stepped-frequency waveform defined by the parameters described above. In various aspects, the radar signal 110-1 is modulated, multiplexed, or filtered using an MMIC 112, which can be implemented as a single MMIC or multiple MMICs. Therefore, the transmitted radar signal 110-1 can be the same as or similar to the waveform detailed above.

[0058] Any parameter used to define the waveform can be predetermined, for example, provided by user input to achieve waveform generation. Any parameter can be stored in memory associated with the radar system for subsequent waveform generation. To generate a waveform or any part of a waveform, any parameter can be retrieved from the memory associated with the waveform. This can include, for example, memory implemented within the radar system or memory communicatively coupled to the radar system via a link or data bus.

[0059] At 504, radar system 104 receives radar echo 110-2 as radar signal 110-1, including a step-frequency waveform from step 502, emitted in field of view 106 and reflected from object 108. The radar echo can be received by radar system 104 at one or more radar sensors. In some implementations, radar system 104 is implemented as part of a sensing system within vehicle 102. In this implementation, radar sensors can be located anywhere on vehicle 102, such as the front, rear, sides, doors, mirrors, etc. In various aspects, radar echo 110-2 can be represented in both a fast time dimension (e.g., samples collected within a single chirp) and a slow time dimension (e.g., samples collected within multiple chirs). When received by radar system 104, radar echo 110-2 is represented in the time domain. One or more processors 114 perform various operations (including analog-to-digital conversion) to generate a digitized radar echo. In some cases, the digital radar echo is generated by the MMIC 112. The digital radar echo is represented in the time domain, where the energy distribution associated with the reflection from object 108 is distributed over multiple time periods.

[0060] At 506, a transformation is performed to determine a two-dimensional representation of radar echo 110-2 in the frequency domain, where the reflection from object 108 is represented at a single or similar frequency. In various aspects, this transformation is performed by processor 114 via execution of radar processing component 118. The two-dimensional representation may include radar echo 110-2 with respect to a fast time dimension and a slow time dimension. The digitized radar echo 110-2 is processed using processor 114 via a two-dimensional Fourier transform (e.g., FFT or DFT). In the frequency space, a peak search may be performed by at least one processor 114 to determine one or more energy peaks. In some implementations, the peak search is performed to distinguish the reflection from object 108 from system noise. Energy peaks can be found, and execution of radar processing component 118 can determine data associated with the energy peaks.

[0061] In various aspects, the transformation used to determine the two-dimensional representation of the radar echo 110-2 in the frequency domain includes phase contribution compensation for the slow time dimension with respect to the target range. In some implementations, the slow time domain is compensated by processor 114 through execution by radar processing component 118. In various aspects, the phase can be compensated using the following equation based on the frequency change of the k-th chirp, the speed of light, and the target range: For example, radar echo 110-2 can model a field of view with range values ​​extending from 0 to 500 meters. Therefore, the slow time dimension can be compensated for at range values ​​from 0 to 500 meters using the equations described above.

[0062] In some implementations, the radar echo 110-2 contains a portion of interest within the range value of its two-dimensional representation in the frequency domain. In these implementations, the slow-time dimension of the two-dimensional representation is compensated only for the portion of interest in the range value. For example, radar system 104 can obtain an estimate that an object exists near a distance of 150 meters. As a result, radar system 104 can selectively compensate for the slow-time dimension of the two-dimensional representation only between target distances of 130 meters and 160 meters. This implementation can be advantageous when object detection is expected at a specific distance (e.g., in blind spot monitoring).

[0063] At 508, the range and range change rate associated with object 108 in field of view 106 are determined based on the two-dimensional representation of radar echo 110-2 in the frequency domain. For example, one or more energy peaks can be found within the two-dimensional representation of radar echo 110-2 in the frequency domain. In various aspects, one or more energy peaks can be associated with an object in the field of view. For example, object 108 can be represented by a single energy peak in the two-dimensional representation of radar echo 110-2. In another example, object 108 can reflect radar signal 110-1 to create multiple energy peaks from the two-dimensional representation, and these multiple energy peaks can be grouped to represent object 108. In various aspects, the energy peaks determined based on the two-dimensional representation of radar echo 110-2 in the frequency domain can be more accurate and include a reduced probability of false detection or a reduced probability of failing to identify a true detection. Additionally, data including highly accurate range and range change rate of object 108 can be determined for a single energy peak or group of energy peaks.

[0064] Specifically, the frequency of the energy peak can be determined in the fast time dimension, and the frequency can be determined in the slow time dimension. Using the frequencies in the fast and slow time dimensions, radar processing component 118 can be executed to solve a system of two-dimensional equations that produce the range and range change rate of object 108. The two-dimensional equations can be determined from the Fourier transform of the phase response of radar echo 110-2. For example, by defining the frequency change between consecutive chirps, the phase response can be reduced to the following equation: In some implementations, second-order terms are ignored due to their negligible effect relative to first-order terms. The phase response can be represented in the frequency domain by performing a Fourier transform, and the energy peak can be determined. The energy peak can correspond to frequencies in both the fast and slow time dimensions; therefore, a two-dimensional system of equations can be used to determine the distance and rate of change of distance to object 108 associated with the energy peak. Specifically, the frequency in the fast time domain can be expressed as: in, and Similarly, the frequency in the slow time domain after ranging phase compensation can be expressed as:

[0065] In the above equations, f R f represents the ranging frequency (e.g., phase shift per unit distance). DLet represent the Doppler frequency (e.g., the phase shift per unit distance), M represent the sample per chirp, and K represent the chirp per frame. Additionally, the fractional bin index in the fast time dimension and the fractional bin index in the slow time dimension can be represented as p, respectively. * and q * The range and range change rate of object 108 can be solved by using a set of equations associated with the energy peak of the two-dimensional representation of radar echo 110-2 in the frequency domain. Due to the higher signal-to-noise ratio in the two-dimensional representation (due to reduced spectral spread), the range and range change rate determined from the set of equations can be more accurate, and the range change rate can be explicit.

[0066] At 510, data associated with the energy peak in a two-dimensional representation is output to enable radar tracking of object 108. In some implementations, the data associated with the energy peak is output as detection 122. Detection 122 may include information about the position and movement of object 108. In other implementations, the data associated with the energy peak is included within a data cube output. Detection 122, the data cube, or both can be input to radar tracker 120 to determine internal radar tracking. Internal radar tracking can be output to an output interface that parses the internal radar tracking and outputs tracking 124 for radar tracking. In some implementations, tracking 124 is output to the vehicle subsystem of vehicle 102 to assist in the execution of vehicle functions. Example Results

[0067] Figure 6 Example result 600 for a general step-frequency waveform used in a radar system is shown. Result 600 is measured relative to four radar looks. In result 600, multiple radar looks, defined as radar data from independent operations of the radar system, are used to collect amplitude data at multiple input rates. In each look: look A, look B, look C, and look D, the radar system operates at an input rate (e.g., the rate of change of relative velocity or distance between the radar system and the object) between 0 and 100 m / s. It should be noted that result 600 is only simulated for negative input rates; however, due to the symmetry of the Doppler shift, the radar data should appear similar or identical for positive input rates. In other words, whether the distance between the radar system and the object increases or decreases is irrelevant to the current result. In each look, signal strength can be compared based on the amplitude relative to the input rate.

[0068] In observation A, the amplitude is highest at an input rate of 0 m / s, approximately 90.6 dB. As shown, the signal strength (e.g., amplitude) begins to decrease as the input rate increases. For example, at 100 m / s, the peak amplitude is approximately 88.9 dB. Observation B provides similar results, showing the peak amplitude decreasing from approximately 89.1 dB at 0 m / s to approximately 87.3 dB at 100 m / s. Similarly, observation C shows amplitude decay relative to the input rate. Specifically, observation C shows an amplitude of approximately 90.3 dB at 0 m / s and approximately 88.6 dB at 100 m / s. Observation D further illustrates the decrease in amplitude as the input rate decreases. For example, observation D has an amplitude of approximately 89.3 dB at 0 m / s and approximately 88.0 dB at 100 m / s. This decrease in amplitude with increasing input rate leads to spectral spread and reduces the signal-to-noise ratio at high input rates. In various aspects, this can lead to object detection failures or errors in distance and distance change rate determination. For example, the signal amplitude can decrease by about 1 dB per 100 m / s. Furthermore, the lobing structure can be created due to the fractional bin positions in both the fast and slow time dimensions.

[0069] Figure 7 Example results of stepped frequency waveforms for parameter definition of a radar system are shown. Similar to result 600, result 700 is relative to four radar observation measurements: observation A, observation B, observation C, and observation D. These observations were acquired at input rates from 0 to 100 m / s.

[0070] In observation A, the amplitude fluctuates across the input rate; however, the fluctuation is symmetrical across the input rate. Specifically, at high input rates, the amplitude does not appear to decrease asymmetrically. For example, the peak amplitude is almost the same at 0 m / s and 100 m / s, at 70.1 dB. Observation B provides similar results, showing that the amplitude does not decrease asymmetrically with the input rate. For example, the amplitude is almost the same at 0 m / s and 76 m / s, at 72.8 dB. Similarly, observation C shows amplitude decay relative to the input rate. Specifically, observation C shows that the amplitude is almost the same at 11 m / s and 98 m / s, at 76.2 dB. Observation D further shows periodic amplitude relative to the input rate. For example, observation D has almost the same amplitude of 70.2 dB at 0 m / s and 74 m / s. As shown by result 700, the stepped frequency waveform defined for the parameters of the radar system provides the radar response without amplitude decay at high input rates between the target and the radar system. In all aspects, the elimination of coupling terms eliminates the horizontal signal attenuation caused by higher range change rates, thereby enabling accurate detection of objects within the radar system's field of view. In doing so, radar tracking can be performed more robustly, and the radar system allows for safer and more comfortable driving when relying on the autonomous control of the vehicle. Additional examples

[0071] Some additional examples are as follows.

[0072] Example 1. A method comprising: transmitting a radar transmitted signal by a radar system, the radar transmitted signal representing a step-frequency waveform defined by parameters having at least two chirps, the at least two chirps including an initial chirp and a current chirp, wherein a pulse variation between the initial chirp and the current chirp is based on: an initial frequency of the initial chirp; a slope of the initial chirp; an index of the current chirp; and a pulse repetition period of the initial chirp; receiving a radar received signal by the radar system, the radar received signal representing a step-frequency waveform defined by parameters reflected by an object in the field of view of the radar system; performing a transformation on the radar received signal to determine a representation of the radar received signal in the frequency domain; determining a distance and a rate of change of distance associated with an object in the field of view based on the representation of the radar received signal in the frequency domain; and outputting the distance and the rate of change of distance associated with an object in the field of view to a radar tracker to achieve radar tracking of the object in the field of view.

[0073] Example 2. The method described in any of the previous examples, wherein the step frequency waveform defined for the frame parameters further includes a delay time between the start of the current chirp and the start of the frame based on: the start frequency of the initial chirp; the index of the current chirp; and the pulse repetition period of the initial chirp.

[0074] Example 3. A method as described in any of the previous examples, wherein performing a transformation on the radar received signal to determine the representation of the radar received signal in the frequency domain includes: performing a two-dimensional Fourier transform on the radar received signal to generate a two-dimensional representation of the radar received signal in the frequency domain, the two-dimensional representation including a fast time dimension and a slow time dimension.

[0075] Example 4. A method as described in any of the previous examples, wherein determining the distance and range change rate associated with an object in the field of view based on the representation of the radar received signal in the frequency domain includes: determining the peak value of the two-dimensional representation of the radar received signal; and determining the distance and range change rate corresponding to the peak value of the two-dimensional representation of the radar received signal.

[0076] Example 5. A method as described in any of the previous examples, wherein determining the range and range change rate corresponding to the peak of a two-dimensional representation of the radar received signal comprises: determining a fast time frequency and a slow time frequency associated with the peak of the two-dimensional representation of the radar received signal; and determining the range and range change rate corresponding to the fast time frequency and the slow time frequency associated with the peak of the two-dimensional representation.

[0077] Example 6. A method as described in any of the previous examples, wherein performing a transformation on the radar received signal to determine the representation of the radar received signal in the frequency domain further includes: compensating for the phase contribution of the radar received signal in the slow time dimension based on the range value of the two-dimensional representation of the radar received signal.

[0078] Example 7. As described in any of the examples in the preceding examples, the two-dimensional representation of the radar received signal further includes a set of range values; and compensating for the phase contribution of the radar received signal in the slow time dimension based on the range values ​​of the two-dimensional representation of the radar received signal includes: compensating for the slow time dimension of the two-dimensional representation based on a portion of the set of range values ​​of the two-dimensional representation.

[0079] Example 8. A method as described in any of the previous examples, wherein determining the distance and rate of change of distance associated with an object in the field of view based on the representation of the radar received signal in the frequency domain includes ignoring second-order terms.

[0080] Example 9. A method as described in any of the previous examples, where the current chirp is a subsequent chirp emitted after the initial chirp.

[0081] Example 10. The method as described in any of the previous examples further includes determining one or more of the following based on user input: the starting frequency of the initial chirp, the slope of the initial chirp, or the pulse repetition period of the initial chirp.

[0082] Example 11. The method as described in any of the previous examples further includes maintaining one or more of the following in a memory communicating with the radar system: the starting frequency of the initial chirp; the slope of the initial chirp; or the pulse repetition period of the initial chirp.

[0083] Example 12. A method as described in any of the previous examples, wherein transmitting a radar transmit signal representing a stepped frequency waveform defined by parameters includes: obtaining the initial chirp's start frequency, the initial chirp's slope, or the initial chirp's pulse repetition period from a memory communicating with the radar system via a multi-input multi-output integrated circuit of the radar system.

[0084] Example 13. A system comprising: a radar system having at least one processor configured to: transmit a radar transmit signal from the radar system representing a step-frequency waveform having at least two chirps, the at least two chirps including an initial chirp and a current chirp, wherein a pulse variation between the initial chirp and the current chirp is based on: an initial frequency of the initial chirp; a slope of the initial chirp; an index of the current chirp; and a pulse repetition period of the initial chirp; receive a radar receive signal at the radar system representing a step-frequency waveform having parameters defined by reflection from an object in the field of view of the radar system; perform a transformation on the radar receive signal to determine a representation of the radar receive signal in the frequency domain; determine a distance and a rate of change of distance associated with an object in the field of view based on the representation of the radar receive signal in the frequency domain; and output the distance and the rate of change of distance associated with an object in the field of view to a radar tracker to achieve radar tracking of the object in the field of view.

[0085] Example 14. A system as described in any of the previous examples, wherein the step frequency waveform defined for the parameters of a frame further includes a delay time between the start of the current chirp and the start of the frame based on: the start frequency of the initial chirp; the index of the current chirp; and the pulse repetition period of the initial chirp.

[0086] Example 15. A system as described in any of the previous examples, wherein the processor is configured to perform a transformation of a radar received signal to determine a representation of the radar received signal in the frequency domain by performing a two-dimensional Fourier transform on the radar received signal to generate a two-dimensional representation of the radar received signal in the frequency domain, the two-dimensional representation including a fast time dimension and a slow time dimension.

[0087] Example 16. A system as described in any of the previous examples, wherein the processor is configured to determine the distance and range change rate associated with an object in the field of view based on the representation of the radar received signal in the frequency domain by: determining the peak value of the two-dimensional representation of the radar received signal; and determining the distance and range change rate corresponding to the peak value of the two-dimensional representation of the radar received signal.

[0088] Example 17. A system as described in any of the previous examples, wherein the processor is configured to determine the distance and range change rate corresponding to the peak of a two-dimensional representation of a radar received signal by: determining the fast time frequency and slow time frequency associated with the peak of the two-dimensional representation of the radar received signal; and determining the distance and range change rate corresponding to the fast time frequency and slow time frequency associated with the peak of the two-dimensional representation.

[0089] Example 18. A system as described in any of the previous examples, wherein the processor is configured to perform a transformation of the radar received signal to determine the representation of the radar received signal in the frequency domain by compensating for the phase contribution of the radar received signal in the slow time dimension based on the range value of the two-dimensional representation of the radar received signal.

[0090] Example 19. A system as described in any of the previous examples, wherein: the two-dimensional representation of the radar received signal further includes a set of range values; and the processor is configured to compensate for the phase contribution of the radar received signal in the slow time dimension based on the range values ​​of the two-dimensional representation of the radar received signal in such a way that, for a portion of the set of range values, the slow time dimension of the two-dimensional representation is compensated based on that portion of the set of range values.

[0091] Example 20. A system as described in any of the previous examples, wherein the processor is further configured to maintain in the radar system's memory one or more of the following: the initial frequency of the initial chirp; the slope of the initial chirp; or the pulse repetition period of the initial chirp.

[0092] Example 21. A system as described in any of the preceding examples further includes a multiple-input multiple-output integrated circuit configured to: obtain one or more of the initial chirp start frequency, the initial chirp slope, or the pulse repetition period of the initial chirp from the radar system's memory; and generate a parameter-defined step frequency waveform based on one or more of the initial chirp start frequency, the initial chirp slope, or the pulse repetition period of the initial chirp obtained from the memory.

[0093] Example 22. A system as described in any of the previous examples, wherein a radar system is installed in a vehicle.

[0094] Example 23. A system comprising methods for performing as described in any of the previous examples.

[0095] Example 24. A computer-readable storage medium including instructions that, when executed by a processor, cause a radar system to perform the methods described in any of the preceding examples. Conclusion

[0096] While various embodiments of this disclosure have been described in the foregoing description and illustrated in the accompanying drawings, it should be understood that this disclosure is not limited thereto, but can be practiced in various ways within the scope of the following claims. It will be apparent from the foregoing description that various modifications can be made without departing from the spirit and scope of this disclosure as defined by the following claims. Other systems may encounter problems associated with spectral spread and signal attenuation at high range change rates. Therefore, although described with reference to specific radar system elements, the techniques, apparatus, and systems of this disclosure provide plug-and-play compatibility with other radar systems.

[0097] Unless the context explicitly states otherwise, the use of "or" and grammatically related terms indicates an unrestricted, non-exclusive alternative. As used herein, the phrase referring to "at least one" of a list of items means any combination of those items, including a single member. For example, "at least one of a, b, or c" is intended to cover: a, b, c, ab, ac, bc, and abc, as well as any combination with multiple identical elements (e.g., aa, aaa, aab, aac, abb, acc, bb, bbb, bbc, cc, and ccc, or any other ordering of a, b, and c).

Claims

1. A method, the method comprising: A radar system transmits a radar transmission signal representing a frame-specific, parameter-defined step-frequency waveform with at least two chirps, the at least two chirps including an initial chirp and a current chirp within the frame, wherein the transmission of the radar transmission signal representing the parameter-defined step-frequency waveform includes: The pulse frequency of the current chirp, relative to the pulse frequency of the initial chirp, is determined based on the following: the pulse frequency of the current chirp eliminates coupling terms in the frequency domain representation of the radar received signal received in response to the transmission of the radar transmitted signal: The initial frequency of the initial chirp, The slope of the initial chirp, The index of the current chirp, and The pulse repetition period of the initial chirp, wherein the coupling term in the frequency domain representation of the radar received signal causes spectral spread, or a decrease in signal level, or increased noise; and Output the current chirp of the step frequency waveform defined by the parameters, the current chirp having the pulse frequency that eliminates the coupling terms in the frequency domain representation of the radar received signal; The radar system receives a radar received signal, which represents a step frequency waveform defined by the parameters reflected by an object in the field of view of the radar system. Perform a transformation on the radar received signal to determine the representation of the radar received signal in the frequency domain; The distance and rate of change of distance associated with the object in the field of view are determined based on the representation of the radar received signal in the frequency domain. as well as The distance and distance change rate associated with the object in the field of view are output to the radar tracker to achieve radar tracking of the object in the field of view.

2. The method as described in claim 1, characterized in that, The step frequency waveform defined for the parameters of the frame further includes the delay time from the start of the frame of the current chirp based on the following: The initial frequency of the initial chirp; The index of the current chirp; and The pulse repetition period of the initial chirp.

3. The method as described in claim 1, characterized in that, Performing a transformation on the radar received signal to determine the representation of the radar received signal in the frequency domain includes: Perform a two-dimensional Fourier transform on the radar received signal to generate a two-dimensional representation of the radar received signal in the frequency domain, the two-dimensional representation including a fast time dimension and a slow time dimension.

4. The method as described in claim 3, characterized in that, Determining the distance and the rate of change of distance associated with the object in the field of view based on the representation of the radar received signal in the frequency domain includes: Determine the peak value of the two-dimensional representation of the radar received signal; and Determine the distance and the rate of change of distance corresponding to the peak value of the two-dimensional representation of the radar received signal.

5. The method as described in claim 4, characterized in that, Determining the distance and the rate of change of distance corresponding to the peak value of the two-dimensional representation of the radar received signal includes: Determine the fast time frequency and slow time frequency associated with the peak value of the two-dimensional representation of the radar received signal; and Determine the distance and the rate of change of distance corresponding to the fast time frequency and the slow time frequency associated with the peak value in the two-dimensional representation.

6. The method as described in claim 3, characterized in that, Performing a transformation on the radar received signal to determine the representation of the radar received signal in the frequency domain further includes: Based on the distance value of the two-dimensional representation of the radar received signal, the phase contribution of the radar received signal in the slow time dimension is compensated.

7. The method as described in claim 6, characterized in that: The two-dimensional representation of the radar received signal further includes a set of distance values; and The compensation for the phase contribution of the radar received signal in the slow time dimension based on the range value of the two-dimensional representation of the radar received signal includes: For a portion of the set of distance values, the slow time dimension of the two-dimensional representation is compensated based on that portion of the set of distance values ​​in the two-dimensional representation.

8. The method as described in claim 1, characterized in that, Determining the distance and rate of change of distance associated with the object in the field of view based on the representation of the radar received signal in the frequency domain includes ignoring second-order terms.

9. The method as described in claim 1, characterized in that, Further, it includes determining one or more of the following based on user input: the starting frequency of the initial chirp, the slope of the initial chirp, or the pulse repetition period of the initial chirp.

10. The method as described in claim 1, characterized in that, The system further includes maintaining one or more of the following in a memory communicating with the radar system: the starting frequency of the initial chirp, the slope of the initial chirp, or the pulse repetition period of the initial chirp.

11. The method as described in claim 1, characterized in that, The radar transmit signal representing the stepped frequency waveform defined by the parameters includes: The initial frequency of the initial chirp, the slope of the initial chirp, or the pulse repetition period of the initial chirp are obtained from the radar system's multi-input multi-output integrated circuit and from a memory communicating with the radar system.

12. A system comprising: A radar system having at least one processor, the at least one processor being configured to: A radar transmit signal is transmitted from the radar system, the radar transmit signal representing a frame-specific step-frequency waveform with at least two chirps, the at least two chirps including an initial chirp of the frame and a current chirp of the frame, wherein the transmission of the radar transmit signal representing the parameter-defined step-frequency waveform includes: The pulse frequency of the current chirp, relative to the pulse frequency of the initial chirp, is determined based on the following: the pulse frequency of the current chirp eliminates coupling terms in the frequency domain representation of the radar received signal received in response to the transmission of the radar transmitted signal: The initial frequency of the initial chirp, The slope of the initial chirp, The index of the current chirp, and The pulse repetition period of the initial chirp, wherein the coupling term in the frequency domain representation of the radar received signal causes spectral spread, or a decrease in signal level, or increased noise; and Output the current chirp of the step frequency waveform defined by the parameters, the current chirp having the pulse frequency that eliminates the coupling terms in the frequency domain representation of the radar received signal; A radar received signal is received at the radar system, the radar received signal representing a step frequency waveform defined by the parameters reflected by an object in the field of view of the radar system; Perform a transformation on the radar received signal to determine the representation of the radar received signal in the frequency domain; The distance and rate of change of distance associated with the object in the field of view are determined based on the representation of the radar received signal in the frequency domain. as well as The distance and distance change rate associated with the object in the field of view are output to the radar tracker to achieve radar tracking of the object in the field of view.

13. The system as described in claim 12, characterized in that, The step frequency waveform defined for the parameters of the frame further includes the delay time from the start of the frame of the current chirp based on the following: The initial frequency of the initial chirp; The index of the current chirp; and The pulse repetition period of the initial chirp.

14. The system as described in claim 13, characterized in that, The processor is configured to perform a transformation of the radar received signal to determine the representation of the radar received signal in the frequency domain by: Perform a two-dimensional Fourier transform on the radar received signal to generate a two-dimensional representation of the radar received signal in the frequency domain, the two-dimensional representation including a fast time dimension and a slow time dimension.

15. The system as described in claim 14, characterized in that, The processor is configured to determine the distance and the rate of change of distance associated with the object in the field of view based on the representation of the radar received signal in the frequency domain in the following manner: Determine the peak value of the two-dimensional representation of the radar received signal; and Determine the distance and the rate of change of distance corresponding to the peak value of the two-dimensional representation of the radar received signal.

16. The system as described in claim 15, characterized in that, The processor is configured to determine the distance and the rate of change of distance corresponding to the peak value of the two-dimensional representation of the radar received signal in the following manner: Determine the fast time frequency and slow time frequency associated with the peak value of the two-dimensional representation of the radar received signal; and Determine the distance and the rate of change of distance corresponding to the fast time frequency and the slow time frequency associated with the peak value in the two-dimensional representation.

17. The system as claimed in claim 14, characterized in that, The processor is configured to perform a transformation of the radar received signal to determine the representation of the radar received signal in the frequency domain by: The phase contribution of the radar received signal in the slow time dimension is compensated based on the distance value of the two-dimensional representation of the radar received signal.

18. The system as claimed in claim 17, characterized in that: The two-dimensional representation of the radar received signal further includes a set of distance values; and The processor is configured to compensate for the phase contribution of the radar received signal in the slow time dimension based on the distance values ​​of the two-dimensional representation of the radar received signal in such a way that the slow time dimension of the two-dimensional representation is compensated based on the portion of the set of distance values ​​in the two-dimensional representation.

19. The system as claimed in claim 12, characterized in that, The processor is further configured to: The radar system's memory maintains one or more of the initial chirp's starting frequency, the initial chirp's slope, or the initial chirp's pulse repetition period.

20. The system as claimed in claim 12, characterized in that, It further includes a multiple-input multiple-output (MIMO) integrated circuit, the MIMO integrated circuit being configured to: Obtain from the radar system's memory one or more of the initial chirp's starting frequency, the initial chirp's slope, or the initial chirp's pulse repetition period; and The step frequency waveform defined by the parameters is generated based on one or more of the starting frequency of the initial chirp, the slope of the initial chirp, or the pulse repetition period of the initial chirp obtained from the memory.

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